Eurasian Journal of Chemical, Medicinal and Petroleum Research

Abstract Skin cancer, particularly melanoma, poses significant health risks globally. Early detection is crucial for effective treatment and improved patient outcomes. Dermoscopy, a non-invasive imaging technique, has enhanced dermatologists' ability to examine skin lesions. Recent advancements in artificial intelligence (AI), especially deep learning, have shown promising results in automating the analysis of dermoscopic images for skin cancer detection. AI models, particularly convolutional neural networks (CNNs), have been trained on large datasets of dermoscopic images, achieving diagnostic accuracies comparable to or surpassing those of experienced dermatologists. These AI systems can assist in identifying malignant lesions, thereby aiding in early diagnosis and reducing the workload on healthcare professionals. However, challenges remain, including the need for diverse and representative datasets, addressing biases in AI models, and ensuring the clinical applicability of these technologies. This paper reviews the current state of AI applications in dermoscopic image analysis for skin cancer detection, discusses the methodologies employed, evaluates the performance of various AI models, and examines the potential impact on clinical practice. The integration of AI into dermatology holds the promise of enhancing diagnostic accuracy, improving patient outcomes, and optimizing healthcare resources.

Abstract Introduction: Early infection after femoral implant placement is a serious complication influenced by host immunity, wound healing capacity, and nutritional-inflammatory status. Preoperative serum albumin is a practical biomarker that may reflect vulnerability to postoperative infection, but its predictive accuracy remains uncertain in femoral implant surgery. This study aimed to evaluate the sensitivity and specificity of preoperative serum albumin in predicting early infection after femoral implant placement.

Material and methods: This retrospective descriptive cross-sectional study was conducted at Shahid Madani Hospital, Tabriz, on 125 patients selected by convenience sampling. The sample size was estimated using Cochran’s formula. Data were extracted from medical records to evaluate preoperative serum albumin, demographic and clinical variables, operative characteristics, and early postoperative infection after femoral implant placement, with the aim of assessing the diagnostic performance of albumin in predicting early infection.

Results: Among 125 patients, early postoperative infection occurred in 15.2% (19/125). Infected patients had lower preoperative albumin (3.12 ± 0.46 vs 3.66 ± 0.51 g/dL; P < 0.001), a higher rate of hypoalbuminemia (63.2% vs 27.4%; P = 0.002), lower hemoglobin (P = 0.011), and higher inflammatory markers (WBC, P = 0.018; CRP, P = 0.006). Serum albumin predicted infection with good accuracy (cutoff 3.35 g/dL; sensitivity 78.9%, specificity 73.6%, AUC 0.812, P < 0.001).

Conclusion: Preoperative serum albumin appears to be a clinically useful marker for identifying patients at increased risk of early infection after femoral implant placement. Lower albumin levels were consistently associated with infection and showed acceptable diagnostic performance. These findings support incorporating serum albumin into routine preoperative assessment to improve risk stratification and guide perioperative optimization in this surgical population.

Abstract Nanomaterials have emerged as a transformative technology in drug delivery systems, offering unique properties that enhance therapeutic efficacy and safety. Their small size, high surface area, and ability to be engineered for targeted delivery enable improved solubility, controlled release, and reduced side effects of pharmaceuticals. This paper discusses various types of nanomaterials used in drug delivery, including nanoparticles, liposomes, and dendrimers, highlighting their mechanisms of action and advantages over conventional delivery methods. Despite their potential, the integration of nanomaterials in clinical applications faces several challenges, including manufacturing scalability, regulatory hurdles, bio distribution unpredictability, and concerns regarding toxicity and biocompatibility. Additionally, complex interactions between nanomaterials and biological systems pose significant hurdles. The future of nanomaterials in drug delivery lies in innovative approaches, such as personalized medicine and biodegradable carriers, necessitating continued interdisciplinary research and collaboration. This review aims to provide insights into the current status and future perspectives of nanomaterials in drug delivery, emphasizing the importance of overcoming existing challenges to fully harness their potential in enhancing patient outcomes.

Abstract Methods based on atomic behavior, such as molecular dynamics (MD) simulations, are highly accurate for modeling single-layer graphene sheets. However, their high computational cost limits their use to only small-sized systems. This research addresses this limitation by developing a new atomic-scale finite element method (AFEM) based on the Tersoff-Brenner potential to analyze the mechanical properties of graphene. The proposed AFEM method's efficiency and accuracy were demonstrated through a numerical example of a graphene sheet. When compared to MD simulation results, the new method showed very high accuracy. Additionally, its simulation speed was found to be approximately 100 times faster than that of the MD method. This study also investigated the influence of effective factors on simulation speed, such as the initial non-equilibrium bond length and the number of atoms. The AFEM was further developed to incorporate periodic boundary conditions, as these had not been previously considered for nanostructures using this method. The results showed that AFEM modeling without periodic boundary conditions produced results that were very different from those of MD simulations.

Abstract Introduction: Femoral fracture surgery in elderly patients is frequently followed by substantial acute postoperative pain, which may be influenced not only by surgical trauma but also by systemic inflammatory and immune responses. Because the Systemic Immune-Inflammation Index may reflect this biological susceptibility, the present study aimed to pathologically assess its association with the severity of acute postoperative pain after femoral fracture surgery.

Material and methods: This descriptive cross-sectional study was conducted at Shahid Madani Hospital, Tabriz, on 93 elderly patients selected by convenience sampling, with sample size estimated using Cochran’s formula. Demographic, clinical, laboratory, surgical, and postoperative pain data were collected. The Systemic Immune-Inflammation Index was calculated from preoperative platelet, neutrophil, and lymphocyte counts, and its association with acute postoperative pain severity was statistically evaluated.

Results: Patients with severe postoperative pain had markedly higher preoperative SII than those with moderate or mild pain (1801.2±789.6 vs 1280.5±542.7 and 850.2±386.4; P<0.001), along with higher inflammatory markers, lower hemoglobin and albumin, longer operations, greater blood loss, more opioid use, delayed mobilization, and longer hospitalization (all P<0.05). SII correlated with pain intensity (highest 24-hour NRS: r=0.574, P<0.001) and independently predicted severe pain (OR=2.86, 95% CI 1.54-5.31), with good accuracy (AUC=0.812).

Conclusion: Preoperative SII appears to be a clinically useful biomarker for identifying patients at increased risk of severe acute postoperative pain. Its independent association with pain severity and acceptable diagnostic performance suggest that SII may support early perioperative risk stratification and help guide individualized analgesic planning, particularly in patients with an elevated inflammatory burden before surgery.

Abstract The development of renewable energy in Iran is of great importance due to its favorable geographical conditions and the need for sustainable energy sources, and the integration of renewable energy sources in oil and gas operations will create a sustainable future for future generations. The world is at a critical juncture where the demand for energy intersects with the urgent need to combat climate change. Traditional energy sources, dependent on fossil fuels, significantly contribute to greenhouse gas emissions and environmental degradation. In response, there is a paradigm shift towards renewable energy sources such as solar, wind, hydro, and geothermal energy. Programming, in conjunction with technological innovations, plays a pivotal role in the use and optimization of these renewable energy solutions. The role of programming in renewable energy solutions is not just supportive but also transformative. From designing efficient systems and optimizing energy production to enabling smart grids and harnessing the power of artificial intelligence, programming is the main axis that drives the renewable energy revolution forward. As the world increasingly embraces sustainable energy sources, the challenges and opportunities for programming in this area continue to expand. By leveraging the capabilities of programming languages, frameworks, and emerging technologies, developers can help create a cleaner and more sustainable energy future. As we navigate the complexities of climate change, programming becomes an essential tool that enables us to harness the potential of renewable energy and lead the global transition to a more sustainable and resilient energy ecosystem.

Abstract Introduction: Pregnancy-related hormonal and vascular changes may increase nasal mucosal congestion, particularly during the third trimester, when sleep disturbance is also common. Nasal obstruction can promote mouth breathing, nocturnal discomfort, and fragmented sleep. This study aimed to evaluate the effect of NOSE score on sleep quality in primigravid women during the third trimester of pregnancy.

Material and methods: This descriptive cross-sectional study will be conducted at Tabriz University of Medical Sciences in 2026 on 66 primigravid women in the third trimester of pregnancy, selected by convenience sampling. The main variables will include demographic and obstetric characteristics, NOSE score, sleep quality indices, and pregnancy-related sleep disruptors such as nocturia, reflux, back pain, fetal movement-related awakening, and nocturnal breathing discomfort.

Results: Among 66 primigravid women, poor sleep quality was associated with significantly higher NOSE scores than good sleep quality (56.84 ± 18.27 vs. 31.46 ± 14.92, p < 0.001), with severe nasal obstruction occurring more often in poor sleepers (39.47% vs. 10.71%, p = 0.012). NOSE score correlated with worse sleep quality (r = 0.58, p < 0.001) and remained an independent predictor in adjusted analysis (B = 0.07, p = 0.001).

Conclusion: Poor sleep quality in third-trimester primigravid women was significantly associated with greater nasal obstruction severity. Higher NOSE scores independently predicted worse sleep quality, suggesting that nasal symptoms may represent an important and potentially modifiable contributor to sleep disturbance during late pregnancy.

Abstract Introduction: Nasal bone fracture is a common facial injury with potential early postoperative consequences, including pain, bleeding, edema, airway symptoms, and residual deformity. Fracture severity may influence these outcomes by reflecting the extent of structural and soft-tissue damage. This study aimed to determine short-term postoperative complications according to nasal bone fracture severity.

Material and methods: This descriptive cross-sectional study of 75 patients at Tabriz University of Medical Sciences in 2024 investigated the association between nasal bone fracture severity and early outcomes. Measured variables included demographics, fracture characteristics, surgical parameters, and short-term complications, including VAS pain score, epistaxis, edema, ecchymosis, and septal hematoma. Data were analyzed using normality testing, t-tests, Mann-Whitney U, and chi-square tests.

Results: Among 75 patients, severe/complex nasal fractures (n = 34) were associated with worse short-term postoperative outcomes than mild/moderate injuries (n = 41). Severe fracture patients experienced longer operations (41.53 ± 11.47 vs. 28.64 ± 8.12 minutes, p < 0.001), higher 24-hour VAS pain (4.85 ± 1.56 vs. 3.42 ± 1.18, p < 0.001), increased moderate/severe edema (61.76% vs. 26.83%, p = 0.002), and more unplanned visits (26.47% vs. 7.32%, p = 0.027). Severe fracture independently predicted early complications (adjusted OR = 3.86, p = 0.020).

Conclusion: Severe nasal bone fractures are independently associated with an increased risk of short-term postoperative complications. Patients with complex fracture patterns experience higher pain levels, more pronounced soft-tissue edema, and greater rates of early residual deformity, leading to more frequent unplanned clinical evaluations. Preoperative severity stratification can identify high-risk cases requiring closer early postoperative surveillance.

Abstract Macrophages, as central components of the innate immune system, play a pivotal role in orchestrating inflammatory responses. Recent evidence highlights that macrophage function is closely governed by metabolic reprogramming, a process in which shifts in cellular metabolism modulate immune phenotypes and effector functions. During chronic inflammation, macrophages exhibit altered utilization of glycolysis, oxidative phosphorylation (OXPHOS), fatty acid oxidation, and glutamine metabolism. These metabolic shifts determine the polarization state of macrophages, driving pro-inflammatory (M1-like) or anti-inflammatory (M2-like) phenotypes. Persistent metabolic dysregulation contributes to uncontrolled inflammation and tissue damage in chronic diseases such as atherosclerosis, diabetes, rheumatoid arthritis, and cancer. In atherosclerosis, macrophages accumulate lipids and undergo metabolic stress that sustains inflammatory activation. In diabetes, hyperglycemia-induced metabolic reprogramming enhances macrophage glycolysis and inflammatory cytokine production. In tumors, the hypoxic microenvironment reshapes macrophage metabolism to support immunosuppressive and pro-tumorigenic activity. Understanding how metabolic pathways regulate macrophage function reveals therapeutic opportunities. Targeting key enzymes such as hexokinase 2, isocitrate dehydrogenase, or AMP-activated protein kinase (AMPK) offers potential to reprogram macrophages toward inflammation resolution. This review integrates findings from immunometabolism and pathophysiology to demonstrate that macrophage metabolic reprogramming acts as a central mechanism linking cellular metabolism to chronic inflammation and disease progression. Therapeutic strategies that correct macrophage metabolic imbalance may provide novel approaches for managing chronic inflammatory disorders and improving patient outcomes.

Abstract Introduction: Liver transplantation is a life-saving treatment for end-stage liver disease, but its success depends heavily on accurate pathologic assessment before, during, and after surgery. Pathology helps define native liver disease, assess donor organ quality, and identify causes of graft dysfunction. The aim of this study was to evaluate the pathologic findings in patients undergoing liver transplantation.

Material and methods: This retrospective descriptive cross-sectional study was conducted at Imam Reza Hospital, Tabriz, on 73 liver transplant patients selected by convenience sampling based on the Cochran formula. Data were extracted from archived medical records and pathology reports, and included demographic characteristics, transplant indications, explant pathology, and available post-transplant histopathologic findings to evaluate the spectrum of pathologic changes in this patient population.

Results: Among 73 liver transplant recipients, cirrhosis was the leading transplant indication (32.9%) and the dominant explant finding (71.2%), while advanced fibrosis/cirrhosis was present in 75.3%. Steatosis was identified in 31.5%, cholestasis in 23.3%, and hepatocellular carcinoma in 19.2%. Hepatocellular carcinoma was significantly associated with older age (P = 0.041), viral hepatitis (P = 0.018), pre-transplant cirrhosis (P = 0.047), dysplasia (P = 0.006), vascular abnormalities (P = 0.039), and microvascular invasion (P < 0.001).

Conclusion: These findings indicate that end-stage cirrhotic liver disease constitutes the principal pathologic burden in liver transplant recipients, while hepatocellular carcinoma represents a clinically important subset linked to adverse pathologic features. Careful explant pathologic evaluation is therefore essential not only for confirming the underlying disease spectrum but also for identifying malignant and high-risk microscopic characteristics with prognostic relevance.

Abstract Coronaviruses are a large family of viruses that, according to evidence, can cause diseases ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) or even more severe diseases such as Severe Acute Respiratory Syndrome (SARS). Epidemiology A disease, whether contagious or non-contagious, may be more or less common in some areas and under some conditions among a large number of people. In other words, a disease can be more or less common. The science that studies how diseases spread and what causes them to spread is called epidemiology, which is a branch of medical science. Basically, epidemiology seeks to prevent the occurrence and spread of a disease or to control it if it does spread. Communicable diseases are a type of infectious disease that can be transmitted from person to person or to humans through insects and other animals. This disease can also be transmitted by organisms in contaminated water or food that has been exposed to the environment by an infected person. For example, a sick child's cough is one way to transmit a cold or flu to others, which must be well taken care of and prevented. In general, the factors that because infectious diseases include viruses, bacteria, and parasites. The signs and symptoms of infectious diseases will also vary depending on the agent causing the infection.

Abstract Regenerative endodontics is evolving rapidly as an alternative to conventional root canal therapy, aiming not merely to disinfect and fill root canals, but to restore viable pulp tissue with physiological functions such as immune defense, innervation, and dentinogenesis. Central to this paradigm are stem cell–based therapies, which, in concert with scaffolds and signaling factors, offer potential to regenerate the pulp–dentin complex in teeth with necrotic or damaged pulps. This review summarizes the latest progress in the field, focusing on (1) sources of stem cells (e.g. dental pulp stem cells, stem cells from the apical papilla, mesenchymal stem cells of non dental origin, and induced pluripotent stem cells), (2) scaffold design and biomaterial strategies, (3) delivery of growth factors and bioactive cues, (4) cell transplantation vs. cell homing approaches, (5) in vitro, in vivo, and early clinical evidence, and (6) major challenges and future directions. Evidence from animal studies and limited human trials shows promise in root maturation, vascularization, and functional tissue formation. However, full regeneration of the native pulp–dentin architecture — particularly with true odontoblast layer, innervation, and predictable function — remains elusive. Key hurdles include controlling stem cell differentiation and proliferation, immune compatibility, standardized protocols, safety (e.g. tumorigenesis risk), and regulatory issues. Emerging innovations such as cell-free secretomes or exosomes, 3D bioprinting of scaffolds, gene engineering for guided differentiation, and smart biomaterials responsive to microenvironment cues may help overcome current limitations. To accelerate translation toward routine clinical use, rigorous multicenter trials with long-term follow-up, development of GMP grade cell banks, and interdisciplinary collaboration are essential.

Abstract Introduction: Breast cancer remains a major global health burden, and lymph node involvement is a key pathologic indicator of tumor spread, prognosis, and postoperative treatment planning in patients undergoing mastectomy. Accurate nodal assessment also improves disease staging and therapeutic decision-making. This study aims to evaluate the pathologic status of lymph node involvement in patients undergoing mastectomy.

Material and methods: This retrospective descriptive cross-sectional study was conducted at Shahid Madani Hospital in Tabriz on 250 patients selected by convenience sampling, with sample size estimated using Cochran’s formula. Data were extracted from archived medical and pathology records, and clinicopathologic variables, particularly lymph node status and related breast tumor characteristics, were systematically collected and analyzed to evaluate the pattern of nodal involvement in mastectomy patients.

Results: Among 250 mastectomy patients, invasive ductal carcinoma was the predominant subtype (79.2%), most tumors were grade II (57.2%), and mean tumor size was 3.41 ± 1.67 cm. Lymph node involvement was present in 58.4%, with macrometastasis in 51.2% and extranodal extension in 15.6%. Nodal positivity was significantly associated with larger tumor size (3.98 ± 1.78 vs. 2.61 ± 1.14 cm, P < 0.001), higher grade (P = 0.002), and lymphovascular invasion (60.3% vs. 23.1%, P < 0.001).

Conclusion: These findings indicate that lymph node metastasis is common in mastectomy specimens and is closely linked to adverse pathologic features. Larger tumors, higher histologic grade, and lymphovascular invasion appear to be the strongest correlates of nodal spread, underscoring the importance of careful pathologic lymph node assessment for accurate staging, prognostic stratification, and postoperative treatment planning in breast cancer patients.

Abstract Microbiome dysbiosis, an alteration in the composition, diversity, or function of host-associated microbial communities, is increasingly implicated in both gastrointestinal (GI) disorders (e.g., IBS, IBD, colorectal cancer) and systemic metabolic diseases. This study evaluates dysbiosis as a predictive biomarker for incident GI and metabolic disease using integrative multi-omics profiling (16S/shotgun metagenomics, metabolomics, host markers) and machine-learning risk models. We will recruit a prospective cohort (n ≈ 1,000) with baseline stool, blood, and clinical phenotyping and follow participants 3–5 years for disease incidence and progression. Primary outcomes are new diagnoses of IBD, IBS, colorectal neoplasia, NAFLD, and NAFLD; secondary outcomes include changes in glycemic markers, liver enzymes, and bowel-symptom scores. Predictors include alpha/beta diversity, taxon-level signatures (e.g., depletion of butyrate-producers), functional gene modules (SCFA synthesis, bile-acid metabolism, LPS biosynthesis), and metabolite markers (SCFAs, secondary bile acids, trimethylamine N-oxide). Models will adjust for diet, medications (antibiotics, PPIs), BMI, age, and socioeconomic factors. We will validate models internally (cross-validation) and externally (independent cohort). If successful, the work will (1) quantify predictive power of microbiome-derived features beyond traditional risk factors, (2) identify mechanistic microbe–metabolite pathways linking dysbiosis to disease, and (3) provide candidate targets for early intervention. However, clinical translation must consider variability in sampling and current limits of commercial testing; robust standardization and prospective validation are required.

Abstract Introduction: Scaphoid waist nonunion with avascular necrosis is a difficult reconstructive problem because impaired blood supply, instability, and deformity can compromise healing and function. Vascularized grafting has therefore emerged as a biologically appealing option to improve union in selected patients. The aim of this study was to evaluate the early outcomes of the Mathoulin technique in scaphoid waist nonunion with avascular necrosis.

Material and methods: This descriptive cross-sectional study was conducted at Shahid Madani Hospital, Tabriz, with a convenience sample of 50 eligible patients selected using the standard descriptive sample-size formula. Patients underwent evaluation and treatment with the Mathoulin technique, and demographic, clinical, radiographic, and early postoperative outcome variables were recorded to assess short-term surgical results.

Results: The cohort comprised 50 patients (mean age 34.8±9.6 years), predominantly men (64.0%), with avascular necrosis in all cases and a mean nonunion duration of 15.2±6.4 months. After the Mathoulin technique, pain, wrist motion, and grip strength improved significantly (VAS 6.9±1.2 to 2.1 1.0; flexion 41.3±8.7° to 55.6±7.9°; grip strength 19.4±5.3 to 28.7±6.1 kg; all P<0.001), and union was achieved in 88.0% of patients at 11.8±2.6 weeks. Smoking, prior surgery, longer nonunion, severe AVN, and humpback deformity were associated with poorer outcomes.

Conclusion: The Mathoulin technique provided encouraging early clinical and radiographic results for scaphoid waist nonunion with avascular necrosis, with high union rates and significant functional improvement. Outcomes were less favorable in patients with smoking, prior surgery, prolonged nonunion, severe AVN, or deformity, suggesting that careful patient selection remains important.

Abstract Introduction: Pediatric complete forearm fractures may redisplace after closed reduction, potentially causing functional impairment and requiring repeat intervention. Although long-arm and sugar-tong splints can restrict motion and accommodate swelling, the effectiveness of their combined use remains uncertain. This study aimed to evaluate the effect of combined sugar-tong and long-arm splinting on fracture displacement in children with complete forearm fractures.

Material and methods: This randomized clinical trial at Shohada Hospital, Tabriz, evaluated 50 children with complete forearm fractures requiring closed reduction (25 per group, calculated via the two-independent-means formula). Participants were randomly assigned to combined sugar-tong and long-arm splinting or standard long-arm splinting alone. Serial radiographs were obtained from post-reduction through early follow-up to evaluate changes in fracture angulation and translation between the two immobilization methods.

Results: The combined splint group maintained better alignment than the standard splint group, with lower AP angulation, lateral angulation, translation, and shortening at follow-up (week 1 and 2, all P≤0.001); it also had fewer losses of reduction (8.0% vs. 36.0%,P=0.014) and remanipulations (4.0% vs. 24.0%, P=0.037), while parental satisfaction was higher (8.6±1.1 vs. 6.8±1.5, P<0.001).

Conclusion: Combined sugar-tong and long-arm splinting was more effective than standard splinting in preserving reduction and preventing secondary displacement in children with complete forearm fractures, without increasing complications. This simple immobilization strategy may improve early fracture stability and reduce the need for repeat intervention.

Abstract This study explores the effects of temperature and pressure variations on catalyst degradation mechanisms—specifically catalyst crushing and catalyst cake formation—in a light naphtha isomerization unit. Operating conditions within the range of 200–280°C and 10–35 bar were simulated to evaluate mechanical and physical stress on the catalyst bed. Two performance indices were defined: the Catalyst Crushing Index (CCI) and Catalyst Cake Thickness (CCT). Results revealed that both CCI and CCT increase significantly with rising temperature and pressure, with pressure having a more pronounced impact. Elevated pressure intensified catalyst compaction, while temperature contributed to structural weakening and sintering. The analysis showed that high-pressure environments above 25 bar and temperatures exceeding 260°C led to accelerated crushing and cake buildup, contributing to pressure drop, pore blockage, and reduced hydrogen diffusion. These degradation mechanisms ultimately reduce catalytic activity and operational efficiency. The findings suggest that maintaining optimal reactor conditions and incorporating real-time monitoring systems are essential for preventing early catalyst failure. This research provides a predictive framework for improving catalyst performance and life cycle in isomerization processes and can support operational decision-making in refinery settings.

Abstract Pre-participation screening and evaluation is an effective strategy for predicting and preventing injuries in athletes before participating in organized sports. Sports injuries are very difficult and dangerous experiences that athletes face during their sports activities. Even after recovery, psychological factors such as fear of movement and anxiety can affect the return to sports. The aim of the study was to compare fear of movement or re-injury and anxiety caused by pain in athletes with and without a history of musculoskeletal injuries. Another problem that leads to injury in high-level athletes, especially national and professional athletes, is overuse of the spine, various organs and joints of the body, without considering sufficient recovery time. Depletion of energy reserves and body resources from nutrients and lack of proper replacement, impaired recovery, insufficient or poor quality sleep, abuse of stimulant drugs, anabolic steroids, peptides, along with technical errors, are the main factors in the occurrence of musculoskeletal injuries. Some of the equipment and techniques available in bodybuilding and functional training are used in rehabilitation and are used by sports medicine and rehabilitation specialists. Paying attention to strengthening the core muscles of the body with specific techniques and methods plays an important role in preventing spinal injuries, and specific and precise methods are used to improve the strength and fitness of these areas.

Abstract Background: Performance anxiety is a significant challenge for anesthesia nursing students transitioning to clinical practice, potentially compromising patient safety and professional development. Virtual reality (VR)-based simulation offers immersive, repeatable practice opportunities in a safe environment.

Objective: This randomized controlled trial evaluated the effectiveness of VR-based simulation training compared to traditional simulation methods in reducing performance anxiety and enhancing clinical preparedness among anesthesia nursing students.

Methods: A total of 60 second-year anesthesia nursing students were randomly assigned to either an immersive VR simulation group (n=30) or a traditional task-trainer simulation group (n=30). Outcomes were measured at baseline, immediately post-intervention, and at two-week follow-up using the State-Trait Anxiety Inventory (STAI-S), a clinical performance checklist, and a self-efficacy scale.

Results: The VR group demonstrated significantly greater reductions in state anxiety (mean difference: -8.4, p<0.001) and higher self-efficacy scores (p<0.001) compared to the control group. Clinical performance scores improved significantly in both groups, with the VR group showing superior non-technical skills including crisis management and communication (p=0.003).

Conclusion: VR-based simulation training effectively reduces performance anxiety and improves clinical preparedness in anesthesia nursing students, offering a scalable and accessible educational modality for healthcare training programs.

Abstract Introduction: Acute myocardial infarction remains a leading cause of morbidity and mortality, with impaired myocardial reperfusion and electrical instability playing key roles in adverse outcomes. Atrial conduction abnormalities may reflect ischemic burden and microvascular dysfunction. This study aimed to evaluate the clinical and prognostic significance of atrial electrical indices in relation to reperfusion quality and coronary disease severity.

Material and methods: This retrospective cross‑sectional study included 315 consecutive patients admitted to Shahid Madani Hospital, Tabriz, between March 2023 and March 2024. Clinical, laboratory, electrocardiographic, and angiographic data were extracted from medical records. Standardized ECG measurements, angiographic assessment, and post‑PCI outcomes were analyzed to evaluate electrophysiological and clinical associations.

Results: Among 315 cardiomyopathy patients, ischemic etiology was associated with a significantly higher prevalence of isoelectric T waves in lead aVR compared with non‑ischemic cardiomyopathy (P=0.004 and P=0.030). Other T‑wave amplitude categories showed no significant differences between etiologic groups, nor any significant association with the severity of left ventricular systolic dysfunction (all P>0.05).

Conclusion: This study demonstrates that while traditional cardiovascular risk factors are highly prevalent in patients with cardiomyopathy, T‑wave amplitude in lead aVR provides limited functional insight into left ventricular systolic impairment.

Abstract Genetic technologies in personalized medicine have revolutionized the management of anticoagulant therapy. Despite their vital role in preventing blood clots, these drugs pose numerous challenges in dose adjustment and side effect management due to the varying responses of patients. Genetic analysis has enabled the provision of personalized, safer, and more effective therapy by identifying genetic differences in related genes such as CYP2C9 and VKORC1. By precisely adjusting the dose, reducing side effects, accelerating the treatment process, and reducing costs, this technology not only improves the quality of life of patients but also paves the way for new standards in healthcare. However, challenges such as high costs, limited access, and privacy issues require attention and resolution. In this approach, the genome of the individual in question is compared with reference genomes, and based on the information obtained, the individual can be treated in an appropriate and specific way. In fact, the genetic nature of the individual determines the treatment strategy. One aspect of personalized medicine is the use of pharmacogenomics. In this method, a more appropriate and informed drug is provided by using and knowing the sequence of an individual's genome. In conventional medicine, drugs are often prescribed with the idea that the effect of the drug is the same for everyone, but in fact this is not the case and each person responds differently to the drug depending on the nature of their genome sequence. Therefore, various factors must be taken into account. For example, depending on these sequences, side effects, the required amount of drug, the likelihood of successful treatment, and the prognosis of the disease will all be unique to each individual.

Abstract Cooling systems in thermal power plants play a decisive role in maintaining steam cycle efficiency, enhancing equipment reliability, and reducing maintenance costs. In the present study, the water chemistry and corrosion behaviour in the hybrid (dry-wet) cooling system of a sample thermal power plant were investigated. This plant, with a nominal capacity of 1000 MW, supplies the bulk of its water demand from treated municipal wastewater and employs a combination of dry and wet cooling towers to reduce water consumption. Sampling was conducted on demineralised water, recirculating water of the dry tower, inlet water to heat exchangers, wet tower water, and makeup water. General parameters including pH, electrical conductivity, TDS, temperature, and salinity were measured. Additionally, the concentrations of metallic elements were determined using ICP-MS. The results indicated that the demineralised water exhibits exceptionally high purity and is virtually devoid of metal ions, whereas in the dry cycle, a significant increase in aluminium concentration up to approximately 260 ppb was observed, indicative of active corrosion in the aluminium radiators of the dry tower. In contrast, in the wet tower, the concentrations of calcium, sodium, potassium, silica, copper, and zinc increased markedly, attributable to evaporation, concentration of dissolved solids, and the use of wastewater as make-up water. Comparison of the results with EPRI guidelines revealed that although iron and copper levels fall within acceptable ranges, the elevated aluminium concentration may be regarded as the primary indicator of heat transfer equipment degradation. Accordingly, the revision of the water chemistry control programme, continuous monitoring of dissolved aluminium, and reassessment of the dry tower operating conditions are proposed as the most critical management strategies. The findings of this research can serve as a basis for the development of intelligent corrosion monitoring programmes in power plants equipped with hybrid cooling systems.

Abstract Introduction: Right ventricular pacing is critical for managing bradyarrhythmia but can impair left ventricular function due to dyssynchrony. This study examines the impact of septal versus apical pacing on left ventricular ejection fraction (LVEF) using three-dimensional echocardiography, aiming to determine which approach better preserves cardiac function by maintaining more physiologic ventricular activation.

Material and methods: This randomized historical control study included 60 patients undergoing permanent pacemaker implantation at Shahid Madani Hospital between 2011 and 2013. Patients were assigned to septal or apical right ventricular pacing. Three dimensional echocardiography was used to compare left ventricular volumes and ejection fraction, with blinded assessment and standard statistical analyses to evaluate functional differences between pacing strategies.

Results: Patients with septal right ventricular pacing demonstrated preserved conventional and three‑dimensional ejection fraction with no significant deviation from normal values (P > 0.05). Compared with apical pacing, septal pacing was associated with significantly higher conventional and 3D ejection fraction and less impaired septal longitudinal strain, with a clear intergroup difference in SPSS‑Sep.A (P = 0.001).

Conclusion: This study demonstrates that right ventricular septal pacing is associated with more favorable left ventricular systolic performance compared with apical pacing when assessed using both conventional and three dimensional echocardiography.

Abstract Adverse drug reactions (ADRs) and adverse drug events (ADEs) remain major threats to patient safety in hospitals, particularly among older adults, patients with multimorbidity, individuals exposed to polypharmacy, and patients experiencing rapid changes in physiological status. Conventional pharmacovigilance and medication-monitoring approaches depend heavily on retrospective reporting and clinical recognition, which may delay identification of preventable harm. Artificial intelligence (AI), particularly machine learning (ML), natural language processing, and deep learning, offers opportunities to transform pharmacovigilance from a predominantly reactive process into a predictive and continuously updated safety system. This systematic evidence synthesis examined the performance and clinical implications of AI-based models for predicting ADRs and ADEs among hospitalized patients, with particular attention to nursing practice. Evidence published in major biomedical databases synthesized with emphasis on model performance, predictors, validation, explainability, and implications for medication administration and clinical surveillance. Recent systematic reviews indicate that random forest, gradient boosting, support vector machines, regularized regression, and deep-learning architectures frequently used, with pooled predictive performance generally demonstrating moderate discrimination. A 2025 systematic review specifically examining hospitalized patients reported pooled sensitivity and specificity of 78.1% and 70.6%, respectively, for development-only models, 81.5%, and 79.5% for models undergoing external validation. Contemporary evidence also demonstrates increasing use of longitudinal EHR representations, clinical narratives, nursing documentation, and foundation models. However, heterogeneous outcome definitions, missing-data procedures, limited external validation, class imbalance, alert fatigue, algorithmic bias, and insufficient explainability remain substantial barriers to implementation. AI therefore conceptualized as an augmentation technology rather than a replacement for nurses or other clinicians. Effective implementation requires interdisciplinary governance, transparent algorithms, prospective evaluation, workflow integration, education, and continuous monitoring. Properly implemented, AI-supported ADR prediction may strengthen nursing vigilance, prioritize high-risk patients, improve medication safety, and facilitate earlier clinical intervention.

Abstract Introduction: Right ventricular pacing can alter physiological ventricular activation, potentially leading to mechanical dyssynchrony and regional myocardial dysfunction. Advanced echocardiographic techniques, particularly segmental peak systolic strain analysis, allow sensitive detection of these changes. The aim of this study was to evaluate and compare segmental peak systolic strain in patients with septal versus apical right ventricular pacing.

Material and methods: This randomized clinical study with a historical control design was conducted at Shahid Madani Hospital, Tabriz, between 2011 and 2013. Sixty patients requiring permanent pacing were enrolled by census sampling and allocated to septal or apical right ventricular pacing. Segmental peak systolic strain was assessed using speckle‑tracking echocardiography, with blinded analysis and appropriate statistical comparison between groups.

Results: In this cohort, septal right ventricular pacing demonstrated relatively preserved and homogeneous segmental peak systolic strain compared with apical pacing. Both pacing strategies significantly reduced mid and basal septal strain compared with normal values (p < 0.001), with no significant difference between RVS and RVA in Sep.M and Sep.B (p > 0.05). In contrast, anterior septal angle and motion were significantly altered in RVA compared with RVS and normal reference values (p < 0.05).

Conclusion: This study demonstrates that the site of right ventricular pacing plays a critical role in determining regional left ventricular myocardial mechanics. Although both septal and apical pacing are associated with deviations from physiological strain patterns, septal pacing consistently preserves a more uniform and coordinated deformation profile across myocardial segments.